CRII: RI: RUI: Generating Haptics in Telerobotics through Perception Complementarities during Physical Distancing
CRII: RI: RUI: Generating Haptics in Telerobotics through Perception Complementarities during Physical Distancing
批准号:
2101107
负责人:
Yun-Hsuan Su
金额:
$17.44万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-06-01 至 2024-05-31
中文摘要
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英文摘要
Haptic feedback, the sense of touch and awareness of movement, is a fundamental sensory pathway for human everyday life and plays a particularly essential role in object manipulation. In a physically distanced or miniaturized world, telepresence using robot proxies can assist humans with remote tasks, yet an ongoing issue is the limited haptic capabilities due to the lack of high-fidelity, low-cost haptic interfaces or sensors. As a plethora of information exists in the digital age, mostly through images or video streams, the ability to interpret the sense of touch from vision enables new opportunities. This project explores software solutions that can estimate contact force/torque from visual data and train robots to replicate force sensitive soft body manipulation tasks. This software agent will be trained to transmit real-time force/torque estimation without the need for haptic sensors. Promising application domains include providing surgeons with vision-based haptic feedback during robot-assisted minimally invasive surgery, short term telepresence demand for emergencies or disaster response, and teleoperating a companion robot to perform a haptically enabled virtual hug or a remote handshake. The goal is to create a novel software solution that helps humans stay connected, complete remote tasks through intelligent touch estimation, and lower the barrier to entry for haptic teleoperation by reducing accessibility and hardware requirements. This project leverages preliminary endeavors in vision-based force estimation in robot assisted minimally invasive surgery (RMIS). Meanwhile, the technology will evaluate the accuracy of the artificial force, analyze added benefits or limitations of the artificial haptic information, explore the sim-to-real transfer learning capabilities of the proposed framework through Variational Autoencoder-Generative Adversarial Networks (VAE-GANs) and prioritize cross-robot support by ensuring software compatibility with Robot Operating System (ROS), Collaborative Robotics Toolkit (CRTK) and Asynchronous Multi-Body Framework (AMBF) for dynamic simulation and visualization. The wide spectrum of applications ensure significant potential of this forward looking research to impact telerobotics in soft object manipulation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(7)
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Enhanced U-Net Tool Segmentation using Hybrid Coordinate Representations of Endoscopic Images
使用内窥镜图像的混合坐标表示增强 U-Net 工具分割
DOI:
10.1109/ismr48346.2021.9661519
发表时间:
2021
期刊:
2021 International Symposium on Medical Robotics (ISMR
影响因子:
--
作者:
[Huang, Kevin, Chitrakar, Digesh, Jiang, Wenfan, Su, Yun-Hsuan]
通讯作者:
Su, Yun-Hsuan
Securing Robot-assisted Minimally Invasive Surgery through Perception Complementarities
通过感知互补确保机器人辅助微创手术
DOI:
10.1109/irc.2020.00013
发表时间:
2020
期刊:
Fourth IEEE International Conference on Robotic Computing (IRC
影响因子:
--
作者:
[Su, Yun-Hsuan, Sosnovskaya, Yana, Hannaford, Blake, Huang, Kevin]
通讯作者:
Huang, Kevin
Characterizing Limits of Vision-Based Force Feedback in Simulated Surgical Tool-Tissue Interaction
表征模拟手术工具-组织相互作用中基于视觉的力反馈的局限性
DOI:
10.1109/embc44109.2020.9176658
发表时间:
2020
期刊:
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC
影响因子:
--
作者:
[Huang, Kevin, Chitrakar, Digesh, Mitra, Rahul, Subedi, Divas, Su, Yun-Hsuan]
通讯作者:
Su, Yun-Hsuan
A Deep-Learning Approach to Marble-Burying Quantification: Image Segmentation of Marbles and Bedding
大理石埋藏量化的深度学习方法:大理石和层理的图像分割
DOI:
10.1109/sii55687.2023.10039320
发表时间:
2023
期刊:
2023 IEEE/SICE International Symposium on System Integration (SII
影响因子:
--
作者:
[Zhu, Yicheng, Hudson, Brandon, Chakraborttii, Chandranil, Su, Yun-Hsuan, Huang, Kevin]
通讯作者:
Huang, Kevin
Contact Localization via Active Oscillatory Actuation
通过主动振荡驱动进行接触定位
DOI:
10.1109/sii52469.2022.9708753
发表时间:
2022
期刊:
2022 IEEE/SICE International Symposium on System Integration (SII
影响因子:
--
作者:
[Subedi, Divas, Schoemer, Elizabeth, Chitrakar, Digesh, Su, Yun-Hsuan, Huang, Kevin]
通讯作者:
Huang, Kevin
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